Search alternatives:
typing optimization » routing optimization (Expand Search), drawing optimization (Expand Search), joint optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based typing » based testing (Expand Search), based mapping (Expand Search), based teng (Expand Search)
binary b » binary _ (Expand Search)
b model » _ model (Expand Search), a model (Expand Search), 2 model (Expand Search)
typing optimization » routing optimization (Expand Search), drawing optimization (Expand Search), joint optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based typing » based testing (Expand Search), based mapping (Expand Search), based teng (Expand Search)
binary b » binary _ (Expand Search)
b model » _ model (Expand Search), a model (Expand Search), 2 model (Expand Search)
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ANOVA test result.
Published 2025“…The contributions include developing a baseline Convolutional Neural Network (CNN) that achieves an initial accuracy of 86.29%, surpassing existing state-of-the-art deep learning models. Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …”
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Summary of literature review.
Published 2025“…The contributions include developing a baseline Convolutional Neural Network (CNN) that achieves an initial accuracy of 86.29%, surpassing existing state-of-the-art deep learning models. Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …”
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Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations.
Published 2023“…After <i>K</i> − 2 = 2 steps, the resulting tree is binary and the algorithm stops.</p>…”
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A new fast filtering algorithm for a 3D point cloud based on RGB-D information
Published 2019“…This method aligns the color image to the depth image, and the color mapping image is converted to an HSV image. Then, the optimal segmentation threshold of the V image that is calculated by using the Otsu algorithm is applied to segment the color mapping image into a binary image, which is used to extract the valid point cloud from the original point cloud with outliers. …”
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Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment
Published 2019“…<div><p>An image classification algorithm based on adaptive feature weight updating is proposed to address the low classification accuracy of the current single-feature classification algorithms and simple multifeature fusion algorithms. …”
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Table_1_bSRWPSO-FKNN: A boosted PSO with fuzzy K-nearest neighbor classifier for predicting atopic dermatitis disease.docx
Published 2023“…</p>Methods<p>This paper establishes a medical prediction model for the first time on the basis of the enhanced particle swarm optimization (SRWPSO) algorithm and the fuzzy K-nearest neighbor (FKNN), called bSRWPSO-FKNN, which is practiced on a dataset related to patients with AD. …”
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Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level
Published 2021“…Our algorithm outperforms the nearest neighbor algorithm and is shown to produce matched samples with total distance no larger than twice the optimal distance. …”
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Flowchart scheme of the ML-based model.
Published 2024“…<b>K)</b> Algorithm selection from all models. <b>L)</b> Random forest selection. …”
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Analysis and design of algorithms for the manufacturing process of integrated circuits
Published 2023“…This problem is of the pick-and-place type and is NPhard. The (approximate) solution proposals of state-of-the-art methods include rule-based approaches, genetic algorithms, and reinforcement learning. …”